The sample covariance matrix is a statistical tool used to estimate the covariance between each pair of variables in a dataset, capturing the linear relationship between them. It is crucial in multivariate analysis, providing insights into the variance structure and dependencies among variables, and is widely used in fields like finance, machine learning, and data science for tasks such as portfolio optimization and principal component analysis.