This paper demonstrates a novel approach to recurrent neural networks using the natural spatiotemporal dynamics of light in multimode optical fibers. The system processes temporal data with high energy efficiency by leveraging passive light propagation and inherent optical nonlinearities, achieving competitive performance across diverse temporal and spatiotemporal learning tasks without trainable optical parameters.