Multigrid methods are numerical algorithms for solving differential equations that efficiently accelerate the convergence of iterative solvers by operating across multiple scales or grid resolutions. They achieve this by smoothing errors on fine grids and correcting them on coarser grids, significantly reducing computational cost and improving performance for large-scale problems.