Describe the feature or idea you want to propose

Mahalanobis Distance is the distance distance that takes Covariance into account. Mahalanobis distance is widely used in cluster analysis and classification techniques. It is also used for multivariate statistical testing and Fisher's Linear Discriminant Anlaysis that is used for supervised classification. You can take a look at the following wikipedia:

https://en.wikipedia.org/wiki/Mahalanobis_distance

Its applications in Time Series Analysis are described in the following papers:

https://sites.cs.ucsb.edu/~yfwang/papers/IEEE_cybernetics_2015.pdf
https://link.springer.com/chapter/10.1007/978-3-319-13731-5_57

I think it would be a good idea to include this in aeon.distances

Describe your proposed solution

Implement it using numpy and numba (which is fairly simple) or wrap scipy.spatial.distance.mahalanobis.

Describe alternatives you've considered, if relevant

No response

Additional context

No response