In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non-causal. While non-causal filters require knowledge of the future, they can be implemented in practice by introducing a short delay. In this paper, we generalize the idea of exploiting non-causality in optimal filter designs to the multichannel scenario. More specifically, a set of optimal, non-causal, multichannel filters for enhancement based on an orthogonal decomposition is proposed. The evaluation shows that there is a potential gain in noise reduction and signal distortion by introducing non-causality. Moreover, experiments on real-life speech show that we can improve the perceptual quality. ; In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non-causal. While non-causal filters require knowledge of the future, they can be implemented in practice by introducing a short delay. In this paper, we generalize the idea of exploiting non-causality in optimal filter designs to the multichannel scenario. More specifically, a set of optimal, non-causal, multichannel filters for enhancement based on an orthogonal decomposition is proposed. The evaluation shows that there is a potential gain in noise reduction and signal distortion by introducing non-causality. Moreover, experiments on real-life speech show that we can improve the perceptual quality.