PERF: Index.take to check for full range indices
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/v2.3.0.rst` file if fixing a bug or adding a new feature.


```
import pandas as pd
import numpy as np

N = 1_000_000
idx = pd.Index(np.arange(N))
indices = np.arange(N)

%timeit idx.take(indices)

# 11.1 ms ± 271 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)   -> main
# 1.33 ms ± 279 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)  -> PR
```

Motivating use-case:

```
idx1 = pd.Index(np.tile(np.arange(1000), 1000))
idx2 = pd.Index(np.arange(100))

%timeit idx1.join(idx2, how="left")

# 132 ms ± 1.43 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)  -> main
# 110 ms ± 587 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)   -> PR
```
Thanks @lukemanley 