Information disorder research overwhelmingly focuses on fabricated or manipulated content (fake news, deepfakes, propaganda) while comparatively neglecting the most pervasive form of distorted information: media bias. Unlike outright falsehoods, media bias operates within the boundaries of factual reporting, distorting public understanding through framing, omission, and word choice rather than fabrication. This makes it harder to detect, harder to regulate, and paradoxically more influential, since it originates from trusted mainstream sources rather than marginal actors. In this position paper, we argue that media bias should be recognized as a first-class category within information disorder frameworks. Drawing on the Wardle and Derakhshan (2017) taxonomy, communication theory, and a systematic review of over 100 studies on automated media bias detection, we demonstrate that current frameworks inadequately account for the systematic distortion of true content. We present a consolidated taxonomy of media bias types organized by linguistic level, compare detection paradigms across the information disorder and media bias communities, and identify four properties that make media bias uniquely dangerous: its scale, its source credibility, the invisibility of omission, and its cumulative normative effect. We conclude with an integrated research agenda grounded in specific gaps identified through the review.