Inhibitory dynamics plays an important role in the information processing of biological spiking neurons, where incoming stimuli weaken the activity level of neurons. Due to the lack of prohibitive physical effects in photonics, the realization of the photonic spiking neuron (PSN) with intrinsic inhibitory dynamics and the application of efficient inhibitory dynamics in the optical domain have been challenging. Herein, we propose a PSN with all-optical inhibitory dynamics, which is achieved by intrinsic backscattering from the unidirectional-emitted semi-conductor ring laser (SRL) to the master laser. The photonic spiking dynamics of the SRL operating in unidirectional mode were investigated, demonstrating the computational properties of the PSN as a leaky integrate-and-fire neuron. We prove that as the backscattering intensity increases, the number of spikes generated under the same input signal decreases. Under the influence of backscattering, the number of spikes fired increases with the input signal rate. In the speech signal classification task, the classification accuracy improves from 89% to 94% under the influence of inhibitory dynamics. This suggests that the presence of inhibitory dynamics helps filter out unwanted interference information. The results show the potential of backscattering-based inhibition dynamics for facilitating advanced neuromorphic information processing.