Power Iteration is an algorithm used to find the Dominant Eigenvalue and corresponding eigenvector of a matrix, particularly effective for Large and sparse matrices. It repeatedly applies the matrix to a vector, normalizing at each step, until convergence is achieved, leveraging the property that the Dominant Eigenvalue dictates the Long-term Behavior of the iterations.