BUG: Nonintuitive behaviour when indexing with a constant boolean function
- [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.

---

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

```python
import pandas as pd
series = pd.Series([1, 2, 3])
x = series[lambda s: s > 2]    # Indexing with a boolean function, works like a charm
y = series[lambda s: True]     # Indexing with a constant boolean function --> results in KeyError: True
```

#### Problem description
I would expect `y` to be equal to `series` in this example, because the callable function passed to `__getitem__` returns True for all items in the Series. The same error arises when using a DataFrame. I know in this example, it seems like the function would be useless, because it would just return `series`, but in my use case the function that is passed to `__getitem__` is actually a 'filter' function argument, and it would be very convenient to just turn off the filter by passing `lambda df: True` as the filter function.

A quick workaround I found useful is:
```python
import numpy as np
y = series[lambda s: np.full(len(s), True)]
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : d9fff2792bf16178d4e450fe7384244e50635733
python           : 3.8.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.3.0-1030-aws
Version          : #32~18.04.1-Ubuntu SMP Tue Jun 30 23:04:16 UTC 2020
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.0
numpy            : 1.19.0
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.1.1
Cython           : 0.29.21
pytest           : 5.4.3
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : None
html5lib         : None
pymysql          : 0.9.3
psycopg2         : 2.8.5 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : None
fsspec           : 0.7.4
fastparquet      : None
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.4.1
sqlalchemy       : 1.3.13
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : None
numba            : 0.50.1

</details>
