diff --git a/doc/source/whatsnew/v1.5.3.rst b/doc/source/whatsnew/v1.5.3.rst
index dae1e9b84cd67..879bad8ccbfb6 100644
--- a/doc/source/whatsnew/v1.5.3.rst
+++ b/doc/source/whatsnew/v1.5.3.rst
@@ -34,6 +34,7 @@ Bug fixes
 - Fixed bug when instantiating a :class:`DataFrame` subclass inheriting from ``typing.Generic`` that triggered a ``UserWarning`` on python 3.11 (:issue:`49649`)
 - Bug in :func:`pivot_table` with NumPy 1.24 or greater when the :class:`DataFrame` columns has nested elements (:issue:`50342`)
 - Bug in :func:`pandas.testing.assert_series_equal` (and equivalent ``assert_`` functions) when having nested data and using numpy >= 1.25 (:issue:`50360`)
+- Bug in :meth:`DataFrameGroupBy.resample` raises ``KeyError`` when getting the result from a key list when resampling on time index (:issue:`50840`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_153.other:
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 0ac43b773bbf9..77fa574a2bd94 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -1238,7 +1238,7 @@ def _gotitem(self, key, ndim, subset=None):
 
         # Try to select from a DataFrame, falling back to a Series
         try:
-            if isinstance(key, list) and self.key not in key:
+            if isinstance(key, list) and self.key not in key and self.key is not None:
                 key.append(self.key)
             groupby = self._groupby[key]
         except IndexError:
diff --git a/pandas/tests/resample/test_resampler_grouper.py b/pandas/tests/resample/test_resampler_grouper.py
index 8aff217cca5c1..579e3ac110b13 100644
--- a/pandas/tests/resample/test_resampler_grouper.py
+++ b/pandas/tests/resample/test_resampler_grouper.py
@@ -497,3 +497,33 @@ def test_groupby_resample_with_list_of_keys():
         ),
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_resample_on_index_with_list_of_keys():
+    # GH 47362
+    df = DataFrame(
+        data={
+            "group": [0, 0, 0, 0, 1, 1, 1, 1],
+            "val": [3, 1, 4, 1, 5, 9, 2, 6],
+        },
+        index=Series(
+            date_range(start="2016-01-01", periods=8),
+            name="date",
+        ),
+    )
+    result = df.groupby("group").resample("2D")[["val"]].mean()
+    expected = DataFrame(
+        data={
+            "val": [2.0, 2.5, 7.0, 4.0],
+        },
+        index=Index(
+            data=[
+                (0, Timestamp("2016-01-01")),
+                (0, Timestamp("2016-01-03")),
+                (1, Timestamp("2016-01-05")),
+                (1, Timestamp("2016-01-07")),
+            ],
+            name=("group", "date"),
+        ),
+    )
+    tm.assert_frame_equal(result, expected)