Bundle methods are optimization techniques used for solving non-differentiable convex optimization problems by iteratively refining a piecewise-linear approximation of the objective function. They are particularly effective for large-scale problems and are known for their robustness and ability to handle complex constraints and nonsmoothness in the objective function.