Second Moment Estimation is a statistical technique used to estimate the variance of a random variable, which is crucial for understanding the distribution's spread around the mean. It is widely used in fields like machine learning and finance to assess risk and variability, often through methods such as the sample variance or more complex algorithms like the Adam optimizer in neural networks.