diff --git a/doc/source/whatsnew/v1.1.3.rst b/doc/source/whatsnew/v1.1.3.rst
index da94e98bc78dd..34595ea4ec50f 100644
--- a/doc/source/whatsnew/v1.1.3.rst
+++ b/doc/source/whatsnew/v1.1.3.rst
@@ -38,7 +38,6 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.apply` with ``raw=True`` and user-function returning string (:issue:`35940`)
 - Fixed regression when setting empty :class:`DataFrame` column to a :class:`Series` in preserving name of index in frame (:issue:`36527`)
 - Fixed regression in :class:`Period` incorrect value for ordinal over the maximum timestamp (:issue:`36430`)
-- Fixed regression when adding a :meth:`timedelta_range` to a :class:``Timestamp`` raised an ``ValueError`` (:issue:`35897`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 4526fb9c8623c..3eaf428bc64b2 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -450,7 +450,7 @@ def _add_datetimelike_scalar(self, other):
         result = checked_add_with_arr(i8, other.value, arr_mask=self._isnan)
         result = self._maybe_mask_results(result)
         dtype = DatetimeTZDtype(tz=other.tz) if other.tz else DT64NS_DTYPE
-        return DatetimeArray._simple_new(result, dtype=dtype, freq=self.freq)
+        return DatetimeArray(result, dtype=dtype, freq=self.freq)
 
     def _addsub_object_array(self, other, op):
         # Add or subtract Array-like of objects
diff --git a/pandas/tests/arithmetic/test_timedelta64.py b/pandas/tests/arithmetic/test_timedelta64.py
index dd9b6269ce5bf..64d3d5b6d684d 100644
--- a/pandas/tests/arithmetic/test_timedelta64.py
+++ b/pandas/tests/arithmetic/test_timedelta64.py
@@ -2136,20 +2136,3 @@ def test_td64arr_pow_invalid(self, scalar_td, box_with_array):
 
         with pytest.raises(TypeError, match=pattern):
             td1 ** scalar_td
-
-
-def test_add_timestamp_to_timedelta():
-    # GH: 35897
-    timestamp = pd.Timestamp.now()
-    result = timestamp + pd.timedelta_range("0s", "1s", periods=31)
-    expected = pd.DatetimeIndex(
-        [
-            timestamp
-            + (
-                pd.to_timedelta("0.033333333s") * i
-                + pd.to_timedelta("0.000000001s") * divmod(i, 3)[0]
-            )
-            for i in range(31)
-        ]
-    )
-    tm.assert_index_equal(result, expected)