Covariate balancing is a statistical technique used to ensure that treatment and control groups in observational studies are comparable on observed covariates, thereby reducing bias in causal inference. It is crucial for improving the validity of estimated treatment effects by making groups similar in terms of their covariate distributions, which helps mimic randomized experimental conditions.