Ignorable missingness refers to a situation in data analysis where the mechanism causing missing data is unrelated to the missing data itself, or it can be appropriately ignored in the analysis process without biasing the results. This assumption simplifies statistical analyses, allowing researchers to proceed using standard techniques as if the data were complete, provided the data is Missing Completely at Random (MCAR) or Missing at Random (MAR).