This lecture explains the concept of convergence order, distinguishing between linear convergence, where the error decreases at each step by a constant factor, and quadratic convergence, where the error decreases at each step by a factor proportional to the square of the error at the previous step. The lecture also discusses the limitations of quadratic convergence when the error is large and the advantages of quadratic convergence over linear convergence when the error is already small. Furthermore, it introduces the concept of generalizing convergence to order P, where the exponent P determines the convergence rate.