Particle Swarm Optimization (PSO) is a computational method inspired by the social behavior of birds and fish to solve optimization problems by iteratively improving a candidate solution with regard to a given measure of quality. It is particularly effective for nonlinear, multidimensional optimization problems where traditional methods struggle due to its ability to explore a wide search space and converge on a global optimum through simple mathematical operations.