A covariate is a variable particular to each participant in a study (or each subject being studied, if it’s not an individual but rather, for example, a clinic) which could potentially influence the outcome.
Deeper dive
The term covariate technically includes the independent variable(s) the researcher is specifically investigating, but most often, in practice, the term refers to potential confounding variables in a study, such as age, sex, income, education, underlying conditions or other characteristics particular to the research area. Covariates and confounders can overlap but are not the same thing.
All confounders definitely affect the outcomes whereas not all covariates do. In some studies, adjusting for covariates does not change the results, showing that those covariates were (usually) not influencing outcomes. If adjusting for covariates does change the results, then some of the covariates adjusted for are also confounders. Also, covariates are explicitly selected, assessed, recorded, and usually calculated in a study. Confounders, on the other hand, may be covariates that were considered in the study, or they may be other variables that were not considered.
Read more on how the term can become confusing here.