NO EVIDENCE BIAS:
A bias that arises from assuming an observation is true because there is no current, or observable evidence to refute it. For example, a study of a new drug may make the claim that the drug is safe because there are no current studies to show that it is harmful. Finding no evidence to refute a conclusion (e.g. observing a non-significant statistical test1), simply means there is no evidence to refute the conclusion, not that the conclusion is true. Academics, media, and conspiracy theorists have all employed No Evidence Bias, in various scenarios to build arguments for why observations may be true.
Because medical science is continuously evolving, and it is not theoretically possible to have the answer to all questions at any given moment, No Evidence Bias can be used to justify any claim, observation, or conclusion, and can therefore be used by any individual on either side of an argument. The observation of no evidence may be due to inappropriately or poorly conduced analyses, and thus cannot be used as an argument to refute a claim unless the analyses are conducted appropriately and without bias. Also see: Confirmation Bias, and Disconfirmation Bias.
Reference:
1. Altman DG. False Reassurance Based on Non-Significant Results. Clin Endosc. 2017;50(6):617. (Link to Reference)