Surrogate modeling is a technique used to approximate complex and computationally expensive simulations or models with simpler, faster-to-compute models. It is widely used in optimization, uncertainty quantification, and sensitivity analysis to reduce computational costs while maintaining sufficient accuracy in predictions.