Gradient descent is an iterative optimization algorithm used to minimize a given function by moving towards the steepest descent direction. The main idea is to start from an initial guess and adjust it iteratively to approach the optimal solution. The algorithm relies on computing the gradient of the function, which indicates the direction of the steepest increase, and then moves in the opposite direction to find the minimum.
