What phenomenon describes a model's test error decreasing, then increasing, and then decreasing again as model capacity grows?

Double Descent

This phenomenon challenges the classical bias-variance tradeoff. It suggests that once a model has enough parameters to interpolate the training data perfectly (the interpolation threshold), increasing capacity further can act as a form of implicit regularization that improves generalization.