diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index 112c401500472..393eb2997f6f0 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -500,7 +500,7 @@ def factorize_array(
     values: np.ndarray,
     na_sentinel: int = -1,
     size_hint: int | None = None,
-    na_value=None,
+    na_value: object = None,
     mask: npt.NDArray[np.bool_] | None = None,
 ) -> tuple[npt.NDArray[np.intp], np.ndarray]:
     """
diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index b06a46dfd1447..a188692a2d8f7 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -460,7 +460,7 @@ def to_numpy(
         self,
         dtype: npt.DTypeLike | None = None,
         copy: bool = False,
-        na_value=lib.no_default,
+        na_value: object = lib.no_default,
     ) -> np.ndarray:
         """
         Convert to a NumPy ndarray.
diff --git a/pandas/core/arrays/masked.py b/pandas/core/arrays/masked.py
index 5ae71b305ac60..90f56a3eea0fb 100644
--- a/pandas/core/arrays/masked.py
+++ b/pandas/core/arrays/masked.py
@@ -337,7 +337,7 @@ def to_numpy(
         self,
         dtype: npt.DTypeLike | None = None,
         copy: bool = False,
-        na_value: Scalar | lib.NoDefault | libmissing.NAType = lib.no_default,
+        na_value: object = lib.no_default,
     ) -> np.ndarray:
         """
         Convert to a NumPy Array.
diff --git a/pandas/core/arrays/numpy_.py b/pandas/core/arrays/numpy_.py
index be7dc5e0ebdc6..36c67d2fe1225 100644
--- a/pandas/core/arrays/numpy_.py
+++ b/pandas/core/arrays/numpy_.py
@@ -368,7 +368,7 @@ def to_numpy(
         self,
         dtype: npt.DTypeLike | None = None,
         copy: bool = False,
-        na_value=lib.no_default,
+        na_value: object = lib.no_default,
     ) -> np.ndarray:
         result = np.asarray(self._ndarray, dtype=dtype)
 
diff --git a/pandas/core/base.py b/pandas/core/base.py
index ce11f31281f5d..12ab942e70574 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -433,7 +433,7 @@ def to_numpy(
         self,
         dtype: npt.DTypeLike | None = None,
         copy: bool = False,
-        na_value=lib.no_default,
+        na_value: object = lib.no_default,
         **kwargs,
     ) -> np.ndarray:
         """
diff --git a/pandas/core/internals/managers.py b/pandas/core/internals/managers.py
index 0a102d4e2bdc9..ded525cd099fc 100644
--- a/pandas/core/internals/managers.py
+++ b/pandas/core/internals/managers.py
@@ -1511,7 +1511,7 @@ def as_array(
         self,
         dtype: np.dtype | None = None,
         copy: bool = False,
-        na_value=lib.no_default,
+        na_value: object = lib.no_default,
     ) -> np.ndarray:
         """
         Convert the blockmanager data into an numpy array.
@@ -1570,7 +1570,7 @@ def as_array(
     def _interleave(
         self,
         dtype: np.dtype | None = None,
-        na_value=lib.no_default,
+        na_value: object = lib.no_default,
     ) -> np.ndarray:
         """
         Return ndarray from blocks with specified item order
diff --git a/pandas/tests/extension/decimal/array.py b/pandas/tests/extension/decimal/array.py
index a3edc95fce96b..6eaa90d7b868a 100644
--- a/pandas/tests/extension/decimal/array.py
+++ b/pandas/tests/extension/decimal/array.py
@@ -105,7 +105,11 @@ def _from_factorized(cls, values, original):
     _HANDLED_TYPES = (decimal.Decimal, numbers.Number, np.ndarray)
 
     def to_numpy(
-        self, dtype=None, copy: bool = False, na_value=no_default, decimals=None
+        self,
+        dtype=None,
+        copy: bool = False,
+        na_value: object = no_default,
+        decimals=None,
     ) -> np.ndarray:
         result = np.asarray(self, dtype=dtype)
         if decimals is not None: