Non-differentiable optimization involves finding the minimum or maximum of functions that are not differentiable at certain points, which poses challenges since traditional gradient-based methods cannot be directly applied. Techniques such as subgradient methods, bundle methods, and proximal algorithms are often employed to handle these optimization problems effectively.