A loss surface is a representation of how a model's loss changes across possible parameter values. Optimization methods such as gradient descent search this surface for parameter settings that reduce loss, often seeking a local or global minimum.
A graph of weight(s) versus loss. Gradient descent aims to find the weight(s) for which the loss surface is at a local minimum.