In regression in R, specifically linear regression in R programming, the "R" variable, also known as the coefficient of determination or R-squared (R²), measures the proportion of the variance in the dependent variable that is predictable from the independent variable(s). It indicates the goodness of fit of the model, ranging from 0 to 1, where 1 represents a perfect fit. Higher values of R indicate a stronger relationship between the variables.