The study of optimal errors of Monte Carlo methods has gained interest in recent years. Since presently no general means are available, the investigation of model problems may help one to understand the mechanisms behind them. The author provides the optimal error for the Monte Carlo integration for input data from a ball of continuous functions. As it turns out, a slight modification of the "crude Monte Carlo method" with fixed cardinality is strictly optimal even among possibly nonlinear Monte Carlo rules with varying cardinality.