Interpreting a covariance matrix involves understanding the magnitude and sign of the covariances. Positive values indicate that two variables increase together, while negative values indicate an inverse relationship. The closer the value is to zero, the weaker the relationship. It's also essential to consider the scale of the variables, as covariance is sensitive to the units of measurement.