BUG: calling at[] on a Series with a single-level MultiIndex returns a Series, not a scalar
- [YES] I have checked that this issue has not already been reported.

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

- [NO] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
idx1 = pd.MultiIndex.from_tuples([(False, 1.0), 
                                  (False, 10.0),
                                  (True, 1.0), 
                                  (True, 10.0)])
s1 = pd.Series((0, 1, 2, 3), index = idx1)
s1.at[(False, 1.0)]   # returns '0', expected output

idx2 = pd.MultiIndex.from_tuples([(False,), (True,)])
s2 = pd.Series((0, 1), index = idx2)
s2.at[False]  # returns a pandas.Series with one element

```

#### Problem description

As per the user guide, I expect `at[]` to return a scalar. However, when I index a `Series` with a `MultiIndex` with only one level, `at[]` returns a `Series` with a single element. A `Series` with a multi-level `MultiIndex` works as expected.


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

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.6.12.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-54-generic
Version          : #60-Ubuntu SMP Fri Nov 6 10:37:59 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 50.3.1.post20201107
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : 1.3.2
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
