This lecture covers the concept of error estimation in Latin Hypercube Sampling (LHS), discussing the generation of LHS, comparison of final estimates, and variance estimation. The instructor explains the idea behind error estimation and the process of generating LHS, emphasizing the importance of comparing final estimates and calculating variance. The lecture also touches on confidence intervals and the significance of accurate variance estimation in LHS.