The Probabilistic Roadmap (PRM) method is a sampling-based algorithm used in robotics and computational geometry to find paths for moving objects in complex environments by constructing a network of feasible paths. It efficiently navigates through high-dimensional spaces by randomly sampling the configuration space and connecting these samples to form a roadmap that captures the connectivity of the space.