BUG: df.groupy().rolling().cov() does not group properly and the cartesian product of all groups is returned instead
- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

```python
import pandas as pd

print(pd.__version__)
df_a = pd.DataFrame({"value": range(10), "idx1": [1] * 5 + [2] * 5, "idx2": [1, 2, 3, 4, 5] * 2}).set_index(["idx1", "idx2"])
df_b = pd.DataFrame({"value": range(5), "idx2": [1, 2, 3, 4, 5]}).set_index("idx2")
test = df_a.groupby(level=0).rolling(2).cov(df_b)
print(test)
```

On pandas 1.3.1:
```python
1.3.1
                value
idx1 idx1 idx2       
1    1    1       NaN
          2       0.5
          3       0.5
          4       0.5
          5       0.5
     2    1       NaN
          2       NaN
          3       NaN
          4       NaN
          5       NaN
2    1    1       NaN
          2       NaN
          3       NaN
          4       NaN
          5       NaN
     2    1       NaN
          2       0.5
          3       0.5
          4       0.5
          5       0.5
```

On pandas 1.0.5:
```python
1.0.5
                value
idx1 idx1 idx2       
1    1    1       NaN
          2       0.5
          3       0.5
          4       0.5
          5       0.5
2    2    1       NaN
          2       0.5
          3       0.5
          4       0.5
          5       0.5
```

1.0.5 has the correct expected output. In 1.3.1, everything in index 1/2/x and 2/1/x is useless and will always be NaN.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : c7f7443c1bad8262358114d5e88cd9c8a308e8aa
python           : 3.9.4.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United States.1252

pandas           : 1.3.1
numpy            : 1.21.1
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 21.1.2
setuptools       : 54.1.2
Cython           : None
pytest           : 6.2.4
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : 2.9.1 (dt dec pq3 ext lo64)
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : 1.4.22
tables           : None
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : None
numba            : None

</details>
