What is the concentration of measure problem in high dimensions?

It describes how distances between points become increasingly similar in high dimensions.

As dimensionality increases, the relative difference between nearest and farthest neighbor distances shrinks. This makes clustering and distance-based algorithms unreliable. Dimensionality reduction helps by projecting data into spaces where distances regain meaningful variation.