Estimation of the bivariate survival function from censored data is considered. The product integral representation of univariate survival functions is generalized to the bivariate case and used to determine identifiability of the survival function of the partially observed data. A bivariate analogue of the Kaplan-Meier estimate is introduced and its almost sure consistency is studied. Extensions to the general multivariate case are sketched.