This lecture discusses the complexity of algorithms by analyzing the growth of functions. It covers the need for precise counting in algorithm efficiency, examples of predicting time for different problem sizes, the estimation of solving time, the relevance of growth rate, and the use of Big-O notation to characterize algorithm efficiency.