The loss landscape represents the graphical depiction of a model's loss function across its parameter space, which helps in understanding how a model's parameters converge during training. Analyzing the structural properties of the loss landscape, such as the presence of minima and saddle points, can provide insights into the optimization challenges and robustness of machine learning models.