diff --git a/doc/source/whatsnew/v2.1.0.rst b/doc/source/whatsnew/v2.1.0.rst
index 62d56f684a11d..64c8f06349449 100644
--- a/doc/source/whatsnew/v2.1.0.rst
+++ b/doc/source/whatsnew/v2.1.0.rst
@@ -423,6 +423,7 @@ Reshaping
 
 Sparse
 ^^^^^^
+- Bug in :class:`SparseDtype` constructor failing to raise ``TypeError`` when given an incompatible ``dtype`` for its subtype, which must be a ``numpy`` dtype (:issue:`53160`)
 - Bug in :meth:`arrays.SparseArray.map` allowed the fill value to be included in the sparse values (:issue:`52095`)
 -
 
diff --git a/pandas/core/arrays/sparse/dtype.py b/pandas/core/arrays/sparse/dtype.py
index dadd161ceeb38..5747ff807600d 100644
--- a/pandas/core/arrays/sparse/dtype.py
+++ b/pandas/core/arrays/sparse/dtype.py
@@ -91,6 +91,9 @@ def __init__(self, dtype: Dtype = np.float64, fill_value: Any = None) -> None:
         dtype = pandas_dtype(dtype)
         if is_string_dtype(dtype):
             dtype = np.dtype("object")
+        if not isinstance(dtype, np.dtype):
+            # GH#53160
+            raise TypeError("SparseDtype subtype must be a numpy dtype")
 
         if fill_value is None:
             fill_value = na_value_for_dtype(dtype)
diff --git a/pandas/tests/arrays/sparse/test_astype.py b/pandas/tests/arrays/sparse/test_astype.py
index 86d69610059b3..d729a31668ade 100644
--- a/pandas/tests/arrays/sparse/test_astype.py
+++ b/pandas/tests/arrays/sparse/test_astype.py
@@ -3,11 +3,7 @@
 
 from pandas._libs.sparse import IntIndex
 
-from pandas import (
-    DataFrame,
-    Series,
-    Timestamp,
-)
+from pandas import Timestamp
 import pandas._testing as tm
 from pandas.core.arrays.sparse import (
     SparseArray,
@@ -135,13 +131,3 @@ def test_astype_dt64_to_int64(self):
         arr3 = SparseArray(values, dtype=dtype)
         result3 = arr3.astype("int64")
         tm.assert_numpy_array_equal(result3, expected)
-
-
-def test_dtype_sparse_with_fill_value_not_present_in_data():
-    # GH 49987
-    df = DataFrame([["a", 0], ["b", 1], ["b", 2]], columns=["A", "B"])
-    result = df["A"].astype(SparseDtype("category", fill_value="c"))
-    expected = Series(
-        ["a", "b", "b"], name="A", dtype=SparseDtype("object", fill_value="c")
-    )
-    tm.assert_series_equal(result, expected)
diff --git a/pandas/tests/arrays/sparse/test_dtype.py b/pandas/tests/arrays/sparse/test_dtype.py
index 58fedbd3e4231..88f8577ded5b0 100644
--- a/pandas/tests/arrays/sparse/test_dtype.py
+++ b/pandas/tests/arrays/sparse/test_dtype.py
@@ -207,3 +207,10 @@ def test_repr():
     result = str(SparseDtype(object, fill_value="0"))
     expected = "Sparse[object, '0']"
     assert result == expected
+
+
+def test_sparse_dtype_subtype_must_be_numpy_dtype():
+    # GH#53160
+    msg = "SparseDtype subtype must be a numpy dtype"
+    with pytest.raises(TypeError, match=msg):
+        SparseDtype("category", fill_value="c")